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Job Description
Structured overview of role & requirementsAbout This Role
Develop, maintain, and optimize scalable data engineering pipelines and feature stores for diverse data types including semi-structured and unstructured data.
Design and implement advanced data transformations, quality checks, and data models to ensure data accuracy, security, and governance.
Integrate data from multiple sources using AWS S3 and SQL data warehouses like Snowflake, supporting AI-driven digital experience and automation solutions.
Minimum Requirements
Minimum 5 years experience in data analysis and engineering.
Bachelor’s degree in Computer Science, Statistics, Informatics, Information Systems, or related quantitative field.
Proficiency with Python, PySpark, SQL, RDBMS, web-crawling/scraping, and ETL/ELT data transformation processes.
Experience with API or stream-based data extraction such as Salesforce API, and hands-on web crawling experience.
Ideal Candidate Profile
Experienced in building end-to-end data engineering solutions handling complex and varied data types (text, images, video, audio).
Skilled in cloud-based data infrastructure, particularly AWS ecosystem (S3, Glue, EMR) and data warehouses like Snowflake, with knowledge of orchestration and streaming tools (Kafka, Spark).
Able to develop and optimize data pipelines with strong focus on data governance, quality, and scalability for AI/ML platform support in network automation context.